Test generation for fault isolation in analog circuits using behavioral models

Cherubal, S.; Chatterjee, Anirban

doi:10.1109/ats.2000.893597

Cited by 3 publications

(1 citation statement)

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“…These methods solve the single fault source diagnosis problem well, while at least two test nodes are required. Behavioral model which can model all possible parameter shifting is proposed in [47]. The required excitation signal is hard to generate.…”

Section: Introductionmentioning

confidence: 99%

Complex Field Fault Modeling-Based Optimal Frequency Selection in Linear Analog Circuit Fault Diagnosis

Yang

Liu

et al. 2014

IEEE Trans. Instrum. Meas.

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Owing to the lack of feasible fault modeling method, hard (open and short) faults, and discretized parametric faults are still the mostly used fault models. These models cannot characterize all soft (parameter shifting) faults because that the parameter of analog element be of continuity character. To address this concern, a complex field fault modeling method is presented first. If fault happens to passive element x i in linear analog circuit, the real (U r ) and imaginary (U j ) parts of faulty voltage phasor U°(U°= U r + j U j ) must satisfy binary quadratic function F i (U r , U j ) = 0, which is independent from the value of element x i and uniquely determined by its location and the nominal circuit under test. Hence, the binary quadratic function can model any continuous parameter shifting (soft) or hard fault. Second, to avoid calculating the explicit expression of binary quadratic function, a simulation-based method is given to obtain the locus of the change in the function F z in the complex plane. Besides, the nominal (fault-free) point, the loci determined by the binary quadratic functions might intersect with each other. It is referred to as aliasing problem in this paper. This problem can be solved by adjusting the frequency of the input signal. Therefore, a constraint optimization method is proposed to select optimal test frequencies. The proposed test generation and compression methods, when combined with the complex field modeling method, can pinpoint much more fault components with less test points and frequencies when compared with the other methods.

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Section: Introductionmentioning

confidence: 99%